Selecting green cover species in the under-trellis zone of Lower Austrian vineyards

Climate change is resulting in more dry and hot summers, accelerating grape ripening and increasing berry sugars concentration. This results in wines with a higher alcohol content, which has a negative impact on wine quality, as well as, on consumer health. Agronomic practices that minimize these effects on berry composition and, consequently, on wine quality must be defined. In this work, different management practices have been assessed on rainfed ‘Monastrell’ grapevines in Jumilla (Murcia, Spain) from 2021 to 2023 vintages. Mulching, shading, application of kaolin and different types of pruning were evaluated, among others field adaptation practices.

Consumption of wine/alcoholic beverages remains a topic of great uncertainty and controversy worldwide. The term “no safe level” dominates the media communication and policy ever since population studies in 2018 [1,2] were published, which denied the existence of a J-curve and suggested that ANY consumption of an alcoholic beverage is harmful to health. The scientific evidence accumulated during the past decades about the health benefits of moderate wine consumption, were questioned and drinking guidelines considered to be too loose.

The Agenda 2030 of the EU sets out the main guidelines for transitioning towards a resilient, green and safe economy. To this regard, the wine sector is experiencing an ecological transition in different ways such as increasing the production of ecological crops, or promoting the production of wines under more environmental-friendly and healthier (i.e., lower levels of SO2) products. These alternatives to conventional production are a smaller proportion of wines, in constant growth and demand, and follow alternative and minority practices, which range from sustainable to deeply philosophical thoughts. Among these methods there are organic, biodynamic and, more recently, natural wines.

The main objective of the work was to develop a simple, robust and selective analytical tool that allows predicting the authenticity of Tempranillo wines from DOCa Rioja. The techniques of voltammetry and absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) spectroscopy have been applied in combination with machine learning (ML) algorithms to classify red wines from DOCa Rioja according to region (Alavesa, Alta or Oriental) and category (young, crianza or reserva).

One of the limitations of vineyards in warm areas is the loss of wine quality due to higher temperatures during the grape ripening period. In order to adapt the vineyards to these new climatic conditions, a possible solution is to delay the ripening process of the grapes towards periods with milder temperatures, by means of management practices and thus improve the quality of the fruit and the wine produced. The technique of severe shoot pruning (SSP) has proven useful in achieving this objective.